The performance of wireless communication is not only limited due to inter-cell interference (ICI). In systems like WCDMA (Wideband Code Division Multiple Access) and LTE (Long Term Evolution), the UE (User Equipment) additionally experiences intra-cell interference due to multi-path and MU-MIMO (Multi-User Multiple Input Multiple Output) interference. Hence, even at high geometries the post-equalization SINR (Signal to Interference plus Noise Ratio) of an interference unaware receiver saturates hence resulting in a high error floor, i.e. in a high block error rate (BLER). In order to guarantee QoS (Quality of Service) the eNodeB (evolved Node B) has to allocate a large fraction of available power or schedule a very low modulation and coding scheme (MCS) and hence reducing cell-edge and cell average throughput. In order to improve the performance, interference aware receivers like interference rejection combining (IRC) or a noise-whitening receiver can be used.
Interference aware receivers suppress the interference and noise vector whose covariance needs to be estimated by a receiver. Receivers employ IRC or noise-whitening methods to estimate the signal covariance matrix.
The quality of the noise covariance estimate often directly depends on the quality of the channel estimates. Existing solutions are designed for static channels, i.e. for flat fading in the frequency domain or time-invariant channels in the time domain. System designers are generally faced with a trade-off between quality of the channel estimate and tracking the channel variations. This limits the applicability of the conventional solutions to low and medium frequency-selective or time varying channels. Conventional solutions for dynamically changing channels show a prohibitively high complexity of the estimation.